345 resultados para Denture, Partial, Removable


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Objective. The aim of this clinical study was to determine the efficacy of Uncaria tomentosa (cat's claw) against denture stomatitis (DS).Study Design. Fifty patients with DS were randomly assigned into 3 groups to receive 2% miconazole, placebo, or 2% U tomentosa gel. DS level was recorded immediately, after 1 week of treatment, and 1 week after treatment. The clinical effectiveness of each treatment was measured using Newton's criteria. Mycologic samples from palatal mucosa and prosthesis were obtained to determinate colony forming units per milliliter (CFU/mL) and fungal identification at each evaluation period.Results. Candida species were identified with HiCrome Candida and API 20C AUX biochemical test. DS severity decreased in all groups (P < .05). A significant reduction in number of CFU/mL after 1 week (P < .05) was observed for all groups and remained after 14 days (P > .05). C albicans was the most prevalent microorganism before treatment, followed by C tropicalis, C glabrata, and C krusei, regardless of the group and time evaluated. U tomentosa gel had the same effect as 2% miconazole gel.Conclusions. U tomentosa gel is an effective topical adjuvant treatment for denture stomatitis.

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A number of studies have demonstrated that simple elastic network models can reproduce experimental B-factors, providing insights into the structure-function properties of proteins. Here, we report a study on how to improve an elastic network model and explore its performance by predicting the experimental B-factors. Elastic network models are built on the experimental C coordinates, and they only take the pairs of C atoms within a given cutoff distance r(c) into account. These models describe the interactions by elastic springs with the same force constant. We have developed a method based on numerical simulations with a simple coarse-grained force field, to attribute weights to these spring constants. This method considers the time that two C atoms remain connected in the network during partial unfolding, establishing a means of measuring the strength of each link. We examined two different coarse-grained force fields and explored the computation of these weights by unfolding the native structures. Proteins 2014; 82:119-129. (c) 2013 Wiley Periodicals, Inc.

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The current study used strain gauge analysis to perform an in vitro evaluation of the effect of axial and non-axial loading on implant-supported fixed partial prostheses, varying the implant placement configurations and the loading points. Three internal hexagon implants were embedded in the center of each polyurethane block with in-line and offset placements. Microunit abutments were connected to the implants using a torque of 20 N.cm, and plastic prosthetic cylinders were screwed onto the abutments, which received standard patterns cast in Co-Cr alloy (n = 10). Four strain gauges (SGs) were bonded onto the surfaces of the blocks, tangentially to the implants: SG 01 mesially to implant 1, SG 02 and SG 03 mesially and distally to implant 2, respectively, and SG 04 distally to implant 3. Each metallic structure was screwed onto the abutments using a 10-N.cm torque, and axial and non-axial loads of 30 kg were applied at 5 predetermined points. The data obtained from the strain gauge analyses were analyzed statistically through the repeated measures analysis of variance and the Tukey test, with a conventional level of significance of P < 0.05. The results showed a statistically significant difference for the loading point (P = 0.0001), with point E (nonaxial) generating the highest microstrain (327.67 mu epsilon) and point A (axial) generating the smallest microstrain (208.93 mu epsilon). No statistically significant difference was found for implant placement configuration (P = 0.856). It was concluded that the offset implant placement did not reduce the magnitude of microstrain around the implants under axial and non-axial loading conditions, although loading location did influence this magnitude.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)